Rapidly evolving genes in pathogens: Methods for detecting positive selection and examples among fungi, bacteria, viruses ...IntroductionMethods for detecting positive selectionMethods for detecting positive selection using divergence data: looking for traces of past positive selectionThe dN/dS ratioVariable dN/dS ratios among different sites in a sequenceVariable dN/dS ratios among different lineages in a phylogenyVariable dN/dS ratios among different sites in a sequence and lineages in a phylogeny: branch-site codon modelsOther improvements to dN/dS-based approachesBeyond the dN/dS approach: amino acid modelsMethods for detecting positive selection using polymorphism data: looking for traces of recent and ongoing positive selectionPopulation differentiation (FST measures): the degree of differentiationSite Frequency Spectrum: an increase in low-frequency allelesLinkage Disequilibrium (LD) and haplotype structure: extended haplotype homozygosity and increased LDMcDonald–Kreitman (MK) test: contrasting silent and replacement substitutionsImprovements and challengesEvidence of positive selection in pathogensEvidence of positive selection in viruses, protists and bacteriaEvidence of positive selection in pathogenic fungiConclusion and future directionsAcknowledgementsReferencesDiscussionRapidly evolving genes in pathogens: Methods for detecting positive selectionand examples among fungi, bacteria, viruses and protistsGabriela Aguiletaa,b, Guislaine Refre´giera,b, Roxana Yocktengc, Elisabeth Fournierd, Tatiana Girauda,b,*aEcologie, Syste´matique et Evolution, Universite´Paris-Sud, F-91405 Orsay cedex, FrancebEcologie, Syste´matique et Evolution, CNRS F-91405 Orsay cedex, FrancecUMR 7205, CNRS-MNHN, Origine, Structure et Evolution de la Biodiversite´,De´partement Syste´matique et Evolution, 16 rue Buffon CP 39, 75005, Paris, FrancedUMR BGPI, TA A 54/K, Campus International de Baillarguet, 34398 Montpellier cedex 5, France1. IntroductionHosts and pathogens are engaged in a never-ending struggle,hosts evolving to escape pathogen infection and pathogensevolving to escape host defences, as illustrated by the Red Queentale. Debate exists, however, about whether this coevolutionprocess unleashes an ‘arms race’, i.e., the occurrence of recurrentselective sweeps that each favours novel resistance and virulencealleles or leads to ‘trench warfare’, i.e., balancing selectionmaintaining stable and long standing polymorphism at lociinvolved in host–pathogen recognition (Bergelson et al., 2001;Chisholm et al., 2006; Tellier and Brown, 2007). Under the ‘trenchwarfare’ model, the same alleles are maintained over long timescales while in the ‘arms race’ model novel alleles are recurrentlydriven to fixation. A high diversity of phenotypes has in fact longbeen observed regarding host resistance or pathogen infectionability depending on host/pathogen genotypes (Thrall et al., 2001;Salvaudon et al., 2005, 2008). The spatial distribution of the hostand pathogen phenotypes (resistance/infection ability) haveprovided valuable information on local adaptation or maladapta-tion (Kaltz et al., 1999; Burdon and Thrall, 2000; Laine, 2006; Sicardet al., 2007), and thereby on coevolutionary processes.More recently, technological and methodological progress hasallowed the detection of footprints of selection directly on genes.For instance, genes assumed to be important in host–pathogencoevolution can be amplified, sequenced and analysed by powerfulmethods to check whether they are indeed targets of selection,what evolutionary forces are at play (e.g., balancing selection orselective sweeps), what the strength of selection is, and whetherselection has been acting in the more or less recent past (Nielsen,2005; Tenaillon and Tiffin, 2007). Such information can provideuseful insights into the processes of coevolution, for instance fordetermining which process, between trench warfare or arms race,is the most frequent (Holub, 2001; Chisholm et al., 2006; Tiffin andMoeller, 2006), or how often selective sweeps occur. ThisInfection, Genetics and Evolution xxx (2009) xxx–xxxARTICLE INFOArticle history:Received 28 October 2008Received in revised form 14 March 2009Accepted 26 March 2009Available online xxxKeywords:Avirulence genesToxinsAntigensEffectorElicitorResistance genesPolymorphismGenomic scanGene-for-geneParasitePlasmodiumABSTRACTThe ongoing coevolutionary struggle between hosts and pathogens, with hosts evolving to escapepathogen infection and pathogens evolving to escape host defences, can generate an ‘arms race’, i.e., theoccurrence of recurrent selective sweeps that each favours a novel resistance or virulence allele that goesto fixation. Host–pathogen coevolution can alternatively lead to a ‘trench warfare’, i.e., balancingselection, maintaining certain alleles at loci involved in host–pathogen recognition over long time scales.Recently, technological and methodological progress has enabled detection of footprints of selectiondirectly on genes, which can provide useful insights into the processes of coevolution. This knowledgecan also have practical applications, for instance development of vaccines or drugs. Here we review themethods for detecting genes under positive selection using divergence data (i.e., the ratio ofnonsynonymous to synonymous substitution rates, dN/dS). We also review methods for detectingselection using polymorphisms, such as methods based on FSTmeasures, frequency s pectrum, linkagedisequilibrium and haplotype structure. In the second part, we review examples where targets ofselection have been identified in pathog ens using these tests. Genes under positive selection inpathogens have mostly been sought among viruses, bacteria and protists, because of their paramountimportance for human health. Another focus is on fungal pathogens owing to their agronomicimportance. We finally discuss promising directions in pathogen studies, such as detecting selection innon-coding regions.ß 2009 Elsevier B.V. All rights reserved.* Corresponding author at: Ecologie, Syste´matique et Evolution, Baˆtiment 360,Universite´Paris-Sud, F-91405 Orsay cedex, France. Tel.: +33 1 39 15 56 69.E-mail address: [email protected] (T. Giraud).G ModelMEEGID-560; No of Pages 15Please cite this article in press as: Aguileta, G., et al., Rapidly evolving genes in pathogens: Methods for detecting positive selection andexamples among fungi, bacteria, viruses and